| Hi-index | 0.00 |
The algorithm of touching string segmentation is concerned in the work. We proposed an example based touching string segmentation algorithm. The supervised learning was used on the labelled examples and the Markov Random Field has been applied on. We used the belief propagation minimization method to select the candidate patches based on the compatibility of the neighbour patches. The output of the MRF after the iterative belief propagation forms a segmentation probability map. The cut position is extracted from the map. The experiment shows that the proposed method is effective.